Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/201771
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dc.contributor.advisorTudela Fernández, Raúl-
dc.contributor.authorRecasens Esparraguera, Pau-
dc.date.accessioned2023-09-06T16:42:21Z-
dc.date.available2023-09-06T16:42:21Z-
dc.date.issued2023-06-
dc.identifier.urihttp://hdl.handle.net/2445/201771-
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2023, Tutor: Raúl Tudela Fernándezca
dc.description.abstractIn this study, a Python algorithm was implemented for calculating ReHo, ALFF, and fALFF from rs-fMRI images using AFNI software for an Alzheimer’s disease rat model. The study included both genetically modified and wild-type rats, with subsets of each undergoing specific training. The effect of neighborhood size on ReHo calculation was studied, and the temporal evolution of the means for each process was analyzed. Comparisons between the different rat groups revealed greater differences in female rat groups compared to male groupsca
dc.format.extent5 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Recasens, 2023-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física-
dc.subject.classificationNeuroimatgecat
dc.subject.classificationPython (Llenguatge de programació)cat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherNeuroimagingeng
dc.subject.otherPython (Computer program language)eng
dc.subject.otherBachelor's theseseng
dc.titleRegional homogeneity, ALFF and fALFF in rs-fMRI in a Alzheimer’s disease rat modeleng
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Física

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